All over the world women and men, adults and children use daily their fingers to produce finger-pushes on all kind of keyboards, mouse or controller devices related to computers, musical instrument, game console or other controlled machines. Fingers are used to push keys on keyboards, to push machine buttons and even to push computer software graphics user interface buttons. Humans in order to communicate with machines use finger-pushes rather than finger-taps. Finger-taps and finger-pushes are different. A finger-tap is very brief while a finger-push generally lasts a certain time; the duration of a finger-push of a key or button is in general longer than the duration of finger-tap and might require applying a minimum force to actuate mechanical keys. Moreover a key-push requires a key, a button or other object or location (physical or virtual) to push, this fact is by itself a limitation of the freedom of the user as the finger needs to reach the location of the key to actuate it, whereas finger-taps are produced spontaneously and freely on any location of a surface.
Sign languages have been used extensively among speech-disabled people. People who can speak also use a variety of gestures to support their communication in particular with speech-disabled persons. However, because of their complexity the expressiveness of hand gestures has not been fully explored for Human-Computer Interaction (HCI). Combinations of simultaneous finger-taps can carry rich information and are fully exploitable by computers. Finger-taps are not intrusive and more convenient for users to interact with computers. Finger-taps can be used in a wide range of applications related to HCI and in particular for effective recognition of sign languages by computers. In order to solve the problem of gesture recognition, a number of researchers choose to work on partitioning the hand gesture into basic elements or primitives that constitute the gesture. Among the difficulties facing such research work are:                the actual determination and characterization of hand gesture primitives,        the reproducibility of the gesture primitives produced by different users and in different environments,        the hand gestures even if they are well characterized and made reproducible they constitute a language vocabulary that is not rich enough and not large enough to ensure full interaction in related applications, and        the larger the hand gesture language vocabulary becomes the slower the execution of the gestures and therefore the slower the interaction becomes.        
These break-to-conquer-approaches attempting to characterize hand gestures correspond to top-to-bottom approaches in the sense that they start from complex hand gestures and try to break them in simple primitive gestures; the chance of success of their exploration is however limited. Extended FFTT by introducing FTLT (Finger Taps Language Technology) provides a new and innovative bottom-to-top approach that starts from finger-taps corresponding to real basic elements or primitives gestures to build a new concept of sign language and a new concept of HCI. Extended FFTT solves the problems related to the top-to-bottom approaches described above; the introduction of FTLT presents the following advantages:                Finger-taps are perfectly characterized and identifiable by appropriate FFTT sensing devices and related technologies.        Finger-taps are perfectly reproducible with different users and in different environments.        Finger-taps created by up to 10 fingers can produce virtually an unlimited number of successions of combinations that can be used to generate a language with a vocabulary large enough and rich enough (there is theatrically no limit) to ensure full interaction in most related applications; and        Finger-tap combinations can be executed very fast, faster than other known sign languages.        